where the \(c\)  is the parameter for normalization, which is the same as Eq.(REF ). This function borrows the idea of BPR [1]}, which maximizes the distance between different clusters (\({ - (1 - \lambda ){d_\text{A}}({z_j},{z_{k^{\prime }}})}, j,k^{\prime } \notin U^\text{cmu}\) ) and minimizes the same cluster pairs (\({\lambda {d_\text{A}}({z_j},{z_{k}})}, j,k \in U^\text{cmu}\) ). \(\lambda \)  is a parameter to tune the importance of different samples.
